Artificial neural networks approach for modeling of Cr(VI) adsorption from aqueous solution by MR, MAC, MS

Abstract

The adsorption ability of Dowex Optipore L493 resin modified with Aliquat 336 (MR), activated carbon modified with Aliquat 336 (MAC) and sawdust modified with Aliquat 336 (MS) for removal of Cr(VI) from aqueous solution in batch system was investigated. The effects of operational parameters such as adsorbent dosage, initial concentration of Cr(VI) ions, pH, temperature and contact time were studied. An artificial neural network (ANN) model was developed to predict the efficiency of Cr(VI) ions removal. The results revealed that the Langmuir isotherm fitted better than the Freundlich isotherm. The rate of adsorption was shown the best fit with the pseudo-second order model. Thermodynamic parameters showed that the adsorption of Cr(VI) adsorption was feasible, spontaneous and exothermic. The comparison of the removal efficiencies of Cr(VI) using ANN model and experimental results showed that ANN model can estimate the behavior of the Cr(VI) removal process under different conditions.